稳定型冠状动脉疾病患者中综合计算机断层扫描血管造影和有创血管造影对中间冠状动脉病变的功能评估
Functional Evaluation of Intermediate Coronary Lesions with Integrated Computed Tomography Angiography and Invasive Angiography in Patients with Stable Coronary Artery Disease.
作者信息
Xue Jingyi, Li Jianqiang, Sun Danghui, Sheng Li, Gong Yongtai, Wang Dingyu, Zhang Song, Zou Yilun, Shi Jing, Xu Wei, An Mengnan, Dai Chenguang, Li Weimin, Zheng Linqun, Vinograd Asiia, Liu Guangzhong, Kong Yihui, Li Yue
机构信息
Department of Cardiology, The First Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin 150001, Heilongjiang Province, China.
Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510000, Guangdong Province, China.
出版信息
J Transl Int Med. 2022 Jun 10;10(3):255-263. doi: 10.2478/jtim-2022-0018. eCollection 2022 Sep.
BACKGROUND AND OBJECTIVES
The hemodynamic evaluation of coronary stenoses undergoes a transition from wire-based invasive measurements to image-based computational assessments. However, fractional flow reserve (FFR) values derived from coronary CT angiography (CCTA) and angiography-based quantitative flow ratio have certain limitations in accuracy and efficiency, preventing their widespread use in routine practice. Hence, we aimed to investigate the diagnostic performance of FFR derived from the integration of CCTA and invasive angiography (FFR) with artificial intelligence assistance in patients with stable coronary artery disease (CAD).
METHODS
Forty stable CAD patients with 67 target vessels (50%-90% diameter stenosis) were included in this single-center retrospective study. All patients underwent CCTA followed by coronary angiography with FFR measurement within 30 days. Both CCTA and angiographic images were combined to generate a three-dimensional reconstruction of the coronary arteries using artificial intelligence. Subsequently, functional assessment was performed through a deep learning algorithm. FFR was used as the reference.
RESULTS
FFR values were significantly correlated with FFR values (r = 0.81, < 0.001, Spearman analysis). Per-vessel diagnostic accuracy of FFR was 92.54%. Sensitivity and specificity in identifying ischemic lesions were 100% and 88.10%, respectively. Positive predictive value and negative predictive value were 83.33% and 100%, respectively. Moreover, the diagnostic performance of FFR was satisfactory in different target vessels and different segment lesions.
CONCLUSIONS
FFR exhibits excellent diagnostic performance of identifying ischemic lesions in patients with stable CAD. Combining CCTA and angiographic imaging, FFR may represent an effective and practical alternative to invasive FFR in selected patients.
背景与目的
冠状动脉狭窄的血流动力学评估正从基于导丝的侵入性测量向基于图像的计算评估转变。然而，冠状动脉CT血管造影（CCTA）得出的血流储备分数（FFR）值以及基于血管造影的定量血流比在准确性和效率方面存在一定局限性，阻碍了它们在常规实践中的广泛应用。因此，我们旨在研究在稳定型冠状动脉疾病（CAD）患者中，借助人工智能辅助将CCTA与侵入性血管造影相结合得出的FFR（iFR）的诊断性能。
方法
本单中心回顾性研究纳入了40例患有稳定型CAD且有67条靶血管（直径狭窄50%-90%）的患者。所有患者均接受了CCTA检查，随后在30天内进行了冠状动脉造影及FFR测量。将CCTA和血管造影图像相结合，利用人工智能生成冠状动脉的三维重建图像。随后，通过深度学习算法进行功能评估。以FFR作为参考标准。
结果
iFR值与FFR值显著相关（r = 0.81，P < 0.001，Spearman分析）。iFR的单支血管诊断准确率为92.54%。识别缺血性病变的敏感性和特异性分别为100%和88.10%。阳性预测值和阴性预测值分别为83.33%和100%。此外，iFR在不同靶血管和不同节段病变中的诊断性能均令人满意。
结论
iFR在识别稳定型CAD患者的缺血性病变方面表现出优异的诊断性能。结合CCTA和血管造影成像，iFR可能是部分患者侵入性FFR的一种有效且实用的替代方法。
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